Electric Transmission Network Expansion Planning with the Metaheuristic Variable Neighbourhood Search
This paper presents a new method to solve the static long-term power transmission network expansion planning (TNEP) problem that uses the metaheuristic variable neighbourhood search (VNS). The TNEP is a large-scale, complex mixed-integer nonlinear programming problem that consists of determining the optimum expansion in the network to meet a forecasted demand. VNS changes structure neighbourhood within a local algorithm and makes the choices of implementation that integrate intensification and/or diversification strategies during the search process. The initial solution is obtained by a heuristic nonlinear mixed integer which takes two Kirchhoff ’ s laws (transportation and the DC models have been used). Several tests are performed on Graver ’ s 6-bus, IEEE 24-bus and Southern Brazilian systems displaying the applicability of the proposed method, and results show that the proposed method has a significant performance in comparison with some studies addressed in common literature.
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Electric Transmission Network Expansion Planning with the Metaheuristic Variable Neighbourhood Search
Semantic Scholar · Engineering · 2019
Abstract
This paper presents a new method to solve the static long-term power transmission network expansion planning (TNEP) problem that uses the metaheuristic variable neighbourhood search (VNS). The TNEP is a large-scale, complex mixed-integer nonlinear programming problem that consists of determining the optimum expansion in the network to meet a forecasted demand. VNS changes structure neighbourhood within a local algorithm and makes the choices of implementation that integrate intensification and/or diversification strategies during the search process. The initial solution is obtained by a heuristic nonlinear mixed integer which takes two Kirchhoff ’ s laws (transportation and the DC models have been used). Several tests are performed on Graver ’ s 6-bus, IEEE 24-bus and Southern Brazilian systems displaying the applicability of the proposed method, and results show that the proposed method has a significant performance in comparison with some studies addressed in common literature.